Project Summary/Abstract. More than 15,000 patients receive lifesaving kidney transplants in the US every year. Nevertheless, complications due to acute and chronic rejection occur frequently and limit the lifespan of kidney transplants. While clinicians strive to monitor transplant patients carefully, diagnostic options remain limited. Diagnosis of rejection in kidney transplantation requires an invasive needle biopsy, and diagnosis of infections is challenging because tests of infection are predominantly limited to testing one pathogen at a time. This proposal outlines radically new precision-medicine approaches to kidney transplant monitoring. We will invent and apply genomic assays with single cell and single molecule resolution to dissect the complex molecular and cellular heterogeneity associated with important immunological and infectious post-transplant complications. Omics analyses will be performed on 700+ urine samples collected from a cohort of kidney transplant recipients, available through collaboration with Dr. Manikkam Suthanthiran. In a first study, we will implement high-throughput single-cell sequencing of cells isolated from the urine of kidney transplant recipients to understand, predict, and diagnose kidney transplant complications. We will investigate the single cell gene expression profiles associated with acute cellular rejection, infection and graft inflammation caused by ischemic and reperfusion injury. This study will take advantage of recent advances in single-cell sequencing that alleviate limitations of cost, scale and ease. Second, we will invent and apply noninvasive measurements of cell-type and tissue-type specific injury in transplanted kidneys via analyses of urinary cell-free DNA (cfDNA). A large number of small fragments of cell-free DNA (cfDNA) are present in urine that are the debris of dead cells. We will apply precision measurements of two types of epigenetic alterations of cfDNA that are highly cell-, tissue- and organ-type specific: cytosine DNA methylation and genome-wide occupancy of DNA-binding factors. These measurements will enable quantifying the cell and tissue types of origin of urinary cfDNA and will provide detailed information about injury associated with kidney transplant complications. Third, we will perform metagenomics analyses of urinary cfDNA to profile the urinary microbiome associated with urinary tract infection, polyomavirus nephropathy and acute rejection. We will test the utility of these measurements to predict, understand and diagnose viral and bacterial infections of the urinary tract. Identification of microbial sequences does not provide functional information about the life-cycle of the detected organism. To gain a functional understanding from measurements of cfDNA, we will develop and implement tools to profile the structure of the circulating microbiome. Successful implementation of these studies will enable studying the biology of post-transplant complications with unprecedented resolution and will lead to novel, noninvasive liquid biopsies to monitor the health of transplanted kidneys.